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We report the case of a 79-year-old woman in good general health aside from early-stage Alzheimer’s disease who was enrolled in a randomized controlled trial of the novel therapeutic monoclonal antibody lecanemab where she was treated with the placebo, and subsequently in the open label extension study where she received lecanemab infusions every two weeks. After the third infusion, she suffered a seizure followed by aphasia and progressively worsening encephalopathy. Magnetic resonance imaging revealed multifocal cerebral edema and an increased burden of cerebral microhemorrhages compared to pre-trial imaging, consistent with Amyloid Related Imaging Abnormality (ARIA). She was treated with an antiepileptic regimen and high-dose intravenous corticosteroids but continued to worsen and expired after five days in the hospital. The family requested an autopsy and consented to evaluation of her brain for research. Post-mortem MRI confirmed extensive microhemorrhagic changes in the temporal, parietal and occipital lobes, some of which were visible on gross inspection of the brain. Autopsy confirmed APOE genotype of E4/E4 and the presence of typical neuropathological features of Alzheimer’s disease along with severe cerebral amyloid angiopathy with inflammatory features, including perivascular lymphocytic infiltrates, reactive macrophages and fibrinoid degeneration of vessel walls. There were deposits of β-amyloid in meningeal vessels and penetrating arterioles with numerous microaneurysms. Cerebral microhemorrhages were associated with arterioles harboring β-amyloid deposits and having degenerative morphologies. We conclude from these results that the patient likely died as a result of severe cerebral amyloid angiopathy with marked microvascular degeneration and meningoencephalitis. Further study of the mechanism of ARIA and the neuropathological changes associated with plaque clearance are needed.

Spatially resolved molecular assays provide high dimensional genetic, transcriptomic, proteomic, and epigenetic information in situ and at various resolutions. Pairing these data across modalities with histological features enables powerful studies of tissue pathology in the context of an intact microenvironment and tissue structure. Increasing dimensions across molecular analytes and samples require new data science approaches to functionally annotate spatially resolved molecular data. A specific challenge is data-driven cross-sample domain detection that allows for analysis within and between consensus tissue compartments across high volumes of multiplex datasets stemming from tissue atlasing efforts. Here, we present MILWRM – multiplex image labeling with regional morphology – a Python package for rapid, multi-scale tissue domain detection and annotation. We demonstrate MILWRM’s utility in identifying histologically distinct compartments in human colonic polyps and mouse brain slices through spatially-informed clustering in two different spatial data modalities. Additionally, we used tissue domains detected in human colonic polyps to elucidate molecular distinction between polyp subtypes. We also explored the ability of MILWRM to identify anatomical regions of mouse brain and their respective distinct molecular profiles.

Neuronal densities vary enormously across sites within a brain. Does the density of the capillary bed accompany the presumably larger energy requirement of sites with more neurons, or with larger neurons, or is energy supply constrained by a mostly homogeneous capillary bed? Here we find evidence for the latter across various sites in the mouse brain and show that as a result, the ratio of capillary cells per neuron, and thus presumably blood and energy supply per neuron, decreases uniformly with increasing neuronal density and therefore smaller average neuronal size across sites. Additionally, we find that local capillary density is also not correlated with local synapse densities, although there is a small but significant correlation between lower neuronal density (and therefore larger neuronal size) and more synapses per neuron within the restricted range of 6,500-9,500 across cortical sites. Further, local variations in the glial/neuron ratio are also not correlated with local variations in number of synapses per neuron or local synaptic densities. These findings suggest that it is not that larger neurons, neurons with more synapses, or even sites with more synapsesdemandmore energy, but simply that larger (and thus fewer) neurons have more energy available per cell, and to its synapses as a whole, than smaller (and thus more numerous) neurons due to competition for limited resources supplied by a capillary bed of fairly homogeneous density throughout the brain.Significance StatementThe brain is an expensive organ and at rest already uses nearly as much energy as during sensory activation. To ultimately determine whether the high energy cost of the brain is driven by an unusually high energy demand by neurons or constrained by capillary density in the organ, we examine whether sites in the mouse brain with more neurons, larger neurons, or more synapses have more capillary supply, and find instead that capillary density is mostly homogeneous across brain structures. We propose that neurons are constrained to using what energy is available, with little evidence for adjustments according to local demand, which explains its high risk of ischemia and vulnerability to states of compromised metabolism, including normal aging.

Because the white matter of the cerebral cortex contains axons that connect distant neurons in the cortical gray matter, the relationship between the volumes of the 2 cortical compartments is key for information transmission in the brain. It has been suggested that the volume of the white matter scales universally as a function of the volume of the gray matter across mammalian species, as would be expected if a global principle of wiring minimization applied. Using a systematic analysis across several mammalian clades, here we show that the volume of the white matter does not scale universally with the volume of the gray matter across mammals and is not optimized for wiring minimization. Instead, the ratio between volumes of gray and white matter is universally predicted by the same equation that predicts the degree of folding of the cerebral cortex, given the clade-specific scaling of cortical thickness, such that the volume of the gray matter (or the ratio of gray to total cortical volumes) divided by the square root of cortical thickness is a universal function of total cortical volume, regardless of the number of cortical neurons. Thus, the very mechanism that we propose to generate cortical folding also results in compactness of the white matter to a predictable degree across a wide variety of mammalian species.

Human evolution is widely thought to have involved a particular expansion of prefrontal cortex. This popular notion has recently been challenged, although controversies remain. Here we show that the prefrontal region of both human and nonhuman primates holds about 8% of cortical neurons, with no clear difference across humans and other primates in the distribution of cortical neurons or white matter cells along the anteroposterior axis. Further, we find that the volumes of human prefrontal gray and white matter match the expected volumes for the number of neurons in the gray matter and for the number of other cells in the white matter compared with other primate species. These results indicate that prefrontal cortical expansion in human evolution happened along the same allometric trajectory as for other primate species, without modification of the distribution of neurons across its surface or of the volume of the underlying white matter. We thus propose that the most distinctive feature of the human prefrontal cortex is its absolute number of neurons, not its relative volume.

The human prefrontal cortex has been considered different in several aspects and relatively enlarged compared to the rest of the cortical areas. Here we determine whether the white and gray matter of the prefrontal portion of the human cerebral cortex have similar or different cellular compositions relative to the rest of the cortical regions by applying the Isotropic Fractionator to analyze the distribution of neurons along the entire anteroposterior axis of the cortex, and its relationship with the degree of gyrification, number of neurons under the cortical surface, and other parameters. The prefrontal region shares with the remainder of the cerebral cortex (except for occipital cortex) the same relationship between cortical volume and number of neurons. In contrast, both occipital and prefrontal areas vary from other cortical areas in their connectivity through the white matter, with a systematic reduction of cortical connectivity through the white matter and an increase of the mean axon caliber along the anteroposterior axis. These two parameters explain local differences in the distribution of neurons underneath the cortical surface. We also show that local variations in cortical folding are neither a function of local numbers of neurons nor of cortical thickness, but correlate with properties of the white matter, and are best explained by the folding of the white matter surface. Our results suggest that the human cerebral cortex is divided in two zones (occipital and non-occipital) that differ in how neurons are distributed across their gray matter volume and in three zones (prefrontal, occipital, and non-occipital) that differ in how neurons are connected through the white matter. Thus, the human prefrontal cortex has the largest fraction of neuronal connectivity through the white matter and the smallest average axonal caliber in the white matter within the cortex, although its neuronal composition fits the pattern found for other, non-occipital areas.

Expansion of the cortical grey matter in evolution has been accompanied by an even faster expansion of the subcortical white matter volume and by folding of the grey matter surface, events traditionally considered to occur homogeneously across mammalian species. Here we investigate how white matter expansion and cortical folding scale across species of rodents and primates as the grey matter gains neurons. We find very different scaling rules of white matter expansion across the two orders, favoring volume conservation and smaller propagation times in primates. For a similar number of cortical neurons, primates have a smaller connectivity fraction and less white matter volume than rodents; moreover, as the cortex gains neurons, there is a much faster increase in white matter volume and in its ratio to grey matter volume in rodents than in primates. Order-specific scaling of the white matter can be attributed to different scaling of average fiber caliber and neuronal connectivity in rodents and primates. Finally, cortical folding increases as different functions of the number of cortical neurons in rodents and primates, scaling faster in the latter than in the former. While the neuronal rules that govern grey and white matter scaling are different across rodents and primates, we find that they can be explained by the same unifying model, with order-specific exponents. The different scaling of the white matter has implications for the scaling of propagation time and computational capacity in evolution, and calls for a reappraisal of developmental models of cortical expansion in evolution.